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Old 04-25-2011, 02:37 AM   #1
kjdsvklow
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Default Windows 7 Discount The Infinite Headaches Of The A

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Does ID presuppose a mechanistic view of nature?

Frequently Raised But Weak Arguments Against Intelligent Design

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Santa Fe Institute economist Brian Arthur believed that much of what we see in global economic patterns can be explained by a process of ‘locking in’ of historical events (1).  Notably, the success of the QWERTY keyboard or the increased sales of the VHS video system over its arch rival Beta Max did not depend so much on any inherent better quality of the winning system but rather on small details in the history of innovation that, over time, lead to the establishment and the overwhelming success of particular technologies (1).  Once such winning technologies became wide-spread, they became a locked and established part of our culture.   
Arthur undoubtedly received much of his insight from long conversations that he had with biophysicist Stuart Kaufman as the two of them thrashed out the concepts of biology and economic policy in an attempt to reconcile both under the umbrella of their unifying theory of complexity (1).  It was clear that a great number of parallels could be drawn between these two otherwise distinct areas of research. 
From an origin of life standpoint, Kauffman has long been unconvinced by the usual crop of prebiotic synthesis experiments.  There is after all no basis upon which to suppose that amino acids and nucleotides could randomly form long polymer chains with specific functions such as we see in the cell (2).  Following such a realization Kauffman became enthralled by the idea that maybe there was a self-organizing process through which compounds could come together in an autocatalytic cycle- a closed cycle of catalysts that converted one molecule to another in a self sustaining fashion (3).  What was interesting about Kauffman’s idea was the manner through which he reached it- a multidisciplinary environment, such as the Santa Fe Institute with economists, political analysts and archaeologists coming together to look for a common thread uniting the emergence of complexity in lost civilizations, economically autonomous states and ultimately life’s biochemistry.
One of Kauffman’s favorite concepts- the ‘adjacent possible’- describes a collection of molecules that are not actually in existence within the universe but are nevertheless one reaction step away from being synthesized (4).  Thus the adjacent possible always exists since, once new molecules are synthesized, there is a new set of molecules that can always be made from these in a single reaction.  Kauffman proposes that, ever since its origin, the earth’s biosphere has been expanding into the adjacent possible as new molecules and compounds have become available (4).  From a thermodynamic stance, the expansion of the biosphere into the adjacent possible would represent a displacement from equilibrium that, according to Kauffman, would provide the necessary chemical potential for driving the actual state of molecular diversity into the infinite adjacent possible.  In other words many diverse molecules would emerge over time amongst which some would have the necessary properties to behave as biological catalysts.  Given enough time, anything could happen. 
While captivating in simplicity and imaginative content, Kauffman’s cogitations on the emergence of life have done precious little to shake off the explanation-critical question of how specificity had arisen within his proposed autocatalytic cycles.  The operative units of such cycles, namely proteins and nucleic acids, could not all exhibit low specificity if a self-reproducing metabolic cycle were to be in any way sustainable.  Philosopher Stephen Meyer’s exegesis on this matter is profoundly relevant.  “It does not follow,Office 2007 Enterprise Key, nor is it the case biochemically “ writes Meyer “that just because some enzymes might function with low specificity, that all the catalytic peptides (or enzymes) needed to establish a self-reproducing metabolic cycle could function with similarly low levels of specificity and complexity” (5).  As Meyer later notes: 
“For the direct autocatalysis of integrated metabolic complexity to occur, a system of catalytic peptide molecules must first achieve a very specific molecular configuration.  This requirement is equivalent to saying that the system must start with a large amount of specified information or specified complexity….Self organizational models either failed to solve the problem of the origin of specified information or they “solved” the problem at the expense of introducing other unexplained sources of information.  Kauffman’s models provided only the best illustration of this latter “displacement problem.”" (5)
Kauffman’s concept of an infinitely expanding adjacent possible dies an early death when one starts dealing with actual numbers.  Consider, for example, the number of possible amino-acid sequences that we can come up with for a protein that is 200 amino acids in length (numbers that are cited by Kauffman himself; 6).  Proteins are made up of 20 different amino acids most of which are precisely arranged so as to attain specific functions.  This means that for a protein that is 200 amino acids long,Microsoft Office 2010, there are approximately 20200 possible ways that these amino acids can be lined up (ie 10260 proteins).  Given that the total number of particles in the known universe is estimated to be around 1080 and considering Kauffman’s own calculation for the total number of reactions since the big bang as being 10193, it is easy to see that the universe has not been around for long enough to cover even a small fraction of these 10260 proteins (6).  In fact, Kauffman posits that it would take 1067 times the current age of the universe to cover all possible protein combinations for a protein of this size (6).
We can forget the idea of ever being able to cover the full panoply of amino-acid combinations for a 200 amino-acid long protein.  Nevertheless can we find solace in the context of the cell where catalytic events may speed up the rates of reaction and thus cram the adjacent possible into the incredibly short?  The answer here is an even flatter no.  To understand why, we must visit another of Kauffman’s key ideas, that of ‘self-organized criticality’ (7).  When we say that cells are subcritical,Windows 7 Discount, what we are really saying is that they have an extremely constrained rate of expansion of molecular diversity- much more constrained than Kauffman’s adjacent possible biosphere.  If it were much faster, cells would invariably die.  We now know that viruses and bacteria are well below this so-called ‘error catastrophe’ (7).
What does this mean for the exploration of the vast molecular space?  Simple- the organization of molecules into a cellular ‘living’ context does nothing to shorten the time required to find those 200 amino-acid long proteins that are going to perform useful functions.  In fact, because of their subcritical state, the search for functional proteins in a cell only becomes more drawn out.  Molecular biologists Jean Jacques Toulmé and Richard Giegé point out how nature just has not had the time to visit the vast extent of combinatorial space that defines the protein world (8).  In true neo-Darwinian style, they nevertheless assure us that the current repertoire of proteins could easily have evolved from a selected few precursors (8).  If that is not blind faith I do not know what is. 
 
Further Reading
M. Mitchell Waldrop (1992), Complexity, The Emerging Science At The Edge Of Order And Chaos, Simon & Schuster, New York, pp. 49
ibid p. 122
ibid p.123
Stuart Kauffman (2000),Windows 7 Code, Investigations,Office Professional 2007 Key, Published by Oxford University Press, New York, p.142-144
Stephen Meyer (2009) Signature In The Cell: DNA And The Evidence For Intelligent Design, Harper Collins Publishers, New York, p.262
ibid, p.142
ibid. pp. 152, 207-209, 216, 244
Jean-Jacques Toulmé and Richard Giegé (1997), Une introduction à la science des ‘aptamères’ ; Atelier de formation INSERM, ‘Strategies combinatoires pour la selection d’oligonucleotides à fonction prédéfinie: applications en biologie
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